def __init__(self, block_images, item_images, mob_images):
"""
Construct a new ViewRouter with appropriate entity id to image file mappings.
Parameters:
block_images (dict<str: str>): A mapping of block ids to their respective images
item_images (dict<str: str>): A mapping of item ids to their respective images
mob_images (dict<str: str>): A mapping of mob ids to their respective images
"""
super().__init__(block_images, item_images, mob_images)
loader = SpriteSheetLoader()
self._images = loader.load_all()
self._mario_count = 0
self._mario_speed = 8
self._player_facing = 1
self._mob_count = {}
self._mob_speed = {}
self._mob_death = {}
self._bouncy_count = {}
self._bouncy_speed = {}
self._bouncy_activated = {}
self._coin_count = {}
self._coin_speed = {}
def setUpClass(self):
print("This setUpClass() method only called once.")
model = load_all()
self.model_IfKnowDebtor = model['IfKnowDebtor']
self.model_CutDebt = model['CutDebt']
self.model_IDClassifier = model['IDClassifier']
self.model_WillingToPay = model['WillingToPay']
self.model_Installment = model['Installment']
self.model_ConfirmLoan = model['ConfirmLoan']
self.df = pd.read_excel('ConfirmLoan.xls')
import time
import json
import loader
import numpy as np
from sklearn.metrics import accuracy_score
from sklearn.experimental import enable_hist_gradient_boosting
from sklearn.ensemble import HistGradientBoostingClassifier
if __name__ == "__main__":
# No randomness is introduced in HGBDT when `X_train` and `X_test`
# are fixed.
n_jobs = -1
load_funcs = loader.load_all()
config = json.load(open("config.json", "r"))
records = []
for dataset, func in load_funcs.items():
if dataset in ("sector"): # run out of memory on sector
continue
if dataset not in config:
msg = "Missing configuration in json file for dataset = {}."
raise RuntimeError(msg.format(dataset))
X_train, y_train, X_test, y_test = func()
n_classes = np.unique(y_train).shape[0]
objective = ('categorical_crossentropy' if n_classes > 2
else 'binary_crossentropy')
# Assign member ids to new members
#
import sys
import os
from pythoncivicrm.pythoncivicrm import CiviCRM
from pythoncivicrm.pythoncivicrm import CivicrmError
from pythoncivicrm.pythoncivicrm import matches_required
from loader import load_all
site_key = os.environ['CIVI_SITE_KEY']
api_key = os.environ['CIVI_API_KEY']
url = os.environ['CIVI_API_URL']
civicrm = CiviCRM(url, site_key, api_key, True)
members = load_all(civicrm, 1, 200)
#run through all contacts and determine the current highest member id
print('Determining highest current member id...');
high_member_id = 0
for member in members:
print('Current member id ' + str(member.member_id))
print('Highest member id ' + str(high_member_id))
if member.member_id > high_member_id:
high_member_id = member.member_id
print('Highest assigned member id is currently ' + str(high_member_id))
exit
#run through all contacts and assign new member ids where necessary
print('Assigning new member ids...');
import sys,os
sys.path.append('../../MLModel/code/OneClickTraining/')
sys.path.append('../../MLModel/code/TreeModelV2/')
import sys,os
loader_path = '../../classifier/loader/'
sys.path.append(loader_path)
from loader import load_all
model_dict=load_all()
from MLModel.code.OneClickTraining.all_model_py import *
from MLModel.code.TreeModelV2.chatbotv1 import *
class chatbot_engine(object):
def __init__(self):
models_list = ['IDClassifier', 'CutDebt', 'IfKnowDebtor', 'WillingToPay', 'Installment', 'ConfirmLoan']
savedModel_path = '../../classifier/saved_Model/{}/main_flow/{}.pkl'
model_dict = {}
for each_model in models_list:
model_dict[each_model] = pickle.load(open(savedModel_path.format(each_model, each_model), 'rb'))
# model_dict[each_model].classify('再说一次')
# model_dict['StopClassifier'] = StopClassifier()
# model_dict['InitClassifier'] = InitClassifier()
# def models():
# models_list = ['IDClassifier', 'CutDebt', 'IfKnowDebtor', 'WillingToPay', 'Installment', 'ConfirmLoan']
# savedModel_path = '../../MLModel/saved_Model/{}/main_flow/{}.pickle'
# model_dict = {}
# from HRX.Test.chatbot_model import models
import sys, os
loader_path = '../../classifier/loader/'
sys.path.append(loader_path)
from loader import load_all
# model_dict=load_all()
import unittest
import HTMLTestRunner # 导入HTMLTestRunner模块
import pandas as pd
all_error = []
columns = ['split_text', 'classifier', 'label', 'predict_label']
import re
model = load_all()
read_path = '../../MLModel/data/{}/mock_up_data_clean_new.csv'
save_path = '/Users/ozintel/Downloads/Tsl_work_file/Collect_project_file/chatbot/cmc/数据清洗2018_7_31/cleaned_data_2018_8_2/intersection_data_process/data_submit'
class chatBotModel(object):
"""Test chatbot_ttest_model.py"""
def __init__(self):
# print("This setUpClass() method only called once.")
# self.model_IfKnowDebtor = model['IfKnowDebtor']
# self.model_CutDebt = model['CutDebt']
# self.model_IDClassifier = model['IDClassifier']
# self.model_WillingToPay = model['WillingToPay']
# self.model_Installment = model['Installment']
